Modular framework for detection of inter-ictal spikes in iEEG

D 2017

Modular framework for detection of inter-ictal spikes in iEEG

KESNER, Filip, Lukas SEKANINA and Milan BRÁZDIL

Basic information

Original name

Modular framework for detection of inter-ictal spikes in iEEG

Authors

KESNER, Filip (203 Czech Republic), Lukas SEKANINA (203 Czech Republic) and Milan BRÁZDIL (203 Czech Republic, guarantor, belonging to the institution)

Edition

New York, 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017, p. 418-421, 4 pp. 2017

Publisher

IEEE

Other information

Language

English

Type of outcome

Stať ve sborníku

Field of Study

30210 Clinical neurology

Country of publisher

United States of America

Confidentiality degree

není předmětem státního či obchodního tajemství

Publication form

printed version "print"

RIV identification code

RIV/00216224:14110/17:00099906

Organization unit

Faculty of Medicine

ISBN

978-1-5090-2809-2

ISSN

DOI

http://dx.doi.org/10.1109/EMBC.2017.8036851

UT WoS

000427085300104

Keywords in English

detection of inter-ictal spikes in iEEG

Abstract

V originále

In this paper, we present a new modular approach for detection of inter-ictal spikes in intracranial iEEG recordings from patients that are suffering from pharmaco-resistant form of epilepsy. This new approach is presented in the form of a detection framework consisting of three primary modules: first level detector, second level feature extractor, and third level detection classifier, where each module is responsible for a specific functionality. This detection framework can be perceived as a three slot system, where modules can be easily plugged in their slots and replaced by a different module or implementation on demand, in order to adapt the quality of detection (measured in terms of sensitivity, precision or inter-recording adaptability) and computational cost. Using complex real-world data sets it was confirmed that the proposed framework provides highly sensitive and precise detection, while it also significantly reduces the computation time.

Citovat

KESNER, Filip, Lukas SEKANINA and Milan BRÁZDIL. Modular framework for detection of inter-ictal spikes in iEEG. In 39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017. New York: IEEE, 2017, p. 418-421. ISBN 978-1-5090-2809-2. Available from: https://dx.doi.org/10.1109/EMBC.2017.8036851.

@inproceedings{1406930,
   author = {Kesner, Filip and Sekanina, Lukas and Brázdil, Milan},
   address = {New York},
   booktitle = {39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017},
   doi = {http://dx.doi.org/10.1109/EMBC.2017.8036851},
   keywords = {detection of inter-ictal spikes in iEEG},
   howpublished = {tištěná verze "print"},
   language = {eng},
   location = {New York},
   isbn = {978-1-5090-2809-2},
   pages = {418-421},
   publisher = {IEEE},
   title = {Modular framework for detection of inter-ictal spikes in iEEG},
   year = {2017}
}

TY  - JOUR
ID  - 1406930
AU  - Kesner, Filip - Sekanina, Lukas - Brázdil, Milan
PY  - 2017
TI  - Modular framework for detection of inter-ictal spikes in iEEG
PB  - IEEE
CY  - New York
SN  - 9781509028092
KW  - detection of inter-ictal spikes in iEEG
N2  - In this paper, we present a new modular approach for detection of inter-ictal spikes in intracranial iEEG recordings from patients that are suffering from pharmaco-resistant form of epilepsy. This new approach is presented in the form of a detection framework consisting of three primary modules: first level detector, second level feature extractor, and third level detection classifier, where each module is responsible for a specific functionality. This detection framework can be perceived as a three slot system, where modules can be easily plugged in their slots and replaced by a different module or implementation on demand, in order to adapt the quality of detection (measured in terms of sensitivity, precision or inter-recording adaptability) and computational cost. Using complex real-world data sets it was confirmed that the proposed framework provides highly sensitive and precise detection, while it also significantly reduces the computation time.
ER  -

KESNER, Filip, Lukas SEKANINA and Milan BRÁZDIL. Modular framework for detection of inter-ictal spikes in iEEG. In \textit{39th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2017}. New York: IEEE, 2017, p.~418-421. ISBN~978-1-5090-2809-2. Available from: https://dx.doi.org/10.1109/EMBC.2017.8036851.

Detailed Information on Publication Record